{
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 爬取丁香园公开的新冠病毒最新的统计数据\n",
    "\n",
    "\n",
    "网站：https://ncov.dxy.cn/ncovh5/view/pneumonia\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "\n",
    "### 例子1\n",
    "\n",
    "获取各个省份历史统计数据，保存到data目录下，存JSON文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import re\n",
    "import requests\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "today = datetime.date.today().strftime('%Y%m%d')\n",
    "\n",
    "def crawl_dxy_data():\n",
    "    \"\"\"\n",
    "    爬取丁香园实时统计数据，保存到data目录下，以当前日期作为文件名，存JSON文件\n",
    "    \"\"\"\n",
    "    response = requests.get('https://ncov.dxy.cn/ncovh5/view/pneumonia') #request.get()用于请求目标网站\n",
    "    print(response.status_code)                                          # 打印状态码\n",
    "    \n",
    "\n",
    "    try:\n",
    "        url_text = response.content.decode()                             #更推荐使用response.content.deocde()的方式获取响应的html页面\n",
    "        #print(url_text)\n",
    "        url_content = re.search(r'window.getAreaStat = (.*?)}]}catch',   #re.search():扫描字符串以查找正则表达式模式产生匹配项的第一个位置 ，然后返回相应的match对象。\n",
    "                                url_text, re.S)                          #在字符串a中，包含换行符\\n，在这种情况下：如果不使用re.S参数，则只在每一行内进行匹配，如果一行没有，就换下一行重新开始;\n",
    "                                                                         #而使用re.S参数以后，正则表达式会将这个字符串作为一个整体，在整体中进行匹配。\n",
    "        texts = url_content.group()                                      #获取匹配正则表达式的整体结果\n",
    "        content = texts.replace('window.getAreaStat = ', '').replace('}catch', '') #去除多余的字符\n",
    "        json_data = json.loads(content)                                         \n",
    "        with open(today + '.json', 'w', encoding='UTF-8') as f:\n",
    "            json.dump(json_data, f, ensure_ascii=False)\n",
    "    except:\n",
    "        print('<Response [%s]>' % response.status_code)\n",
    "\n",
    "        \n",
    "def crawl_statistics_data():\n",
    "    \"\"\"\n",
    "    获取各个省份历史统计数据，保存到data目录下，存JSON文件\n",
    "    \"\"\"\n",
    "    with open(today + '.json', 'r', encoding='UTF-8') as file:\n",
    "        json_array = json.loads(file.read())\n",
    "\n",
    "    statistics_data = {}\n",
    "    for province in json_array:\n",
    "        response = requests.get(province['statisticsData'])\n",
    "        try:\n",
    "            statistics_data[province['provinceShortName']] = json.loads(response.content.decode())['data']\n",
    "        except:\n",
    "            print('<Response [%s]> for url: [%s]' % (response.status_code, province['statisticsData']))\n",
    "\n",
    "    with open(\"statistics_data.json\", \"w\", encoding='UTF-8') as f:\n",
    "        json.dump(statistics_data, f, ensure_ascii=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-5-e70765c1ead7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# 运行函数，获取结果\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mcrawl_dxy_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mcrawl_statistics_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-4-f7d6113cd082>\u001b[0m in \u001b[0;36mcrawl_dxy_data\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0m爬取丁香园实时统计数据\u001b[0m\u001b[0;31m，\u001b[0m\u001b[0m保存到data目录下\u001b[0m\u001b[0;31m，\u001b[0m\u001b[0m以当前日期作为文件名\u001b[0m\u001b[0;31m，\u001b[0m\u001b[0m存JSON文件\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \"\"\"\n\u001b[0;32m----> 7\u001b[0;31m     \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'https://ncov.dxy.cn/ncovh5/view/pneumonia'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m#request.get()用于请求目标网站\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m\u001b[0;34m)\u001b[0m                                          \u001b[0;31m# 打印状态码\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/requests/api.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(url, params, **kwargs)\u001b[0m\n\u001b[1;32m     73\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     74\u001b[0m     \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetdefault\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'allow_redirects'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 75\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'get'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     76\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     77\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/requests/api.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(method, url, **kwargs)\u001b[0m\n\u001b[1;32m     58\u001b[0m     \u001b[0;31m# cases, and look like a memory leak in others.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     59\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0msessions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msession\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 60\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msession\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     61\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     62\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/requests/sessions.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m    531\u001b[0m         }\n\u001b[1;32m    532\u001b[0m         \u001b[0msend_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msettings\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 533\u001b[0;31m         \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0msend_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    534\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    535\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/requests/sessions.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m    644\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    645\u001b[0m         \u001b[0;31m# Send the request\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 646\u001b[0;31m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0madapter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    647\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    648\u001b[0m         \u001b[0;31m# Total elapsed time of the request (approximately)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/requests/adapters.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    447\u001b[0m                     \u001b[0mdecode_content\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    448\u001b[0m                     \u001b[0mretries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax_retries\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m                     \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    450\u001b[0m                 )\n\u001b[1;32m    451\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    598\u001b[0m                                                   \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout_obj\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    599\u001b[0m                                                   \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 600\u001b[0;31m                                                   chunked=chunked)\n\u001b[0m\u001b[1;32m    601\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    602\u001b[0m             \u001b[0;31m# If we're going to release the connection in ``finally:``, then\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    341\u001b[0m         \u001b[0;31m# Trigger any extra validation we need to do.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    342\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 343\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    344\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mSocketTimeout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mBaseSSLError\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    345\u001b[0m             \u001b[0;31m# Py2 raises this as a BaseSSLError, Py3 raises it as socket timeout.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_validate_conn\u001b[0;34m(self, conn)\u001b[0m\n\u001b[1;32m    837\u001b[0m         \u001b[0;31m# Force connect early to allow us to validate the connection.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    838\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'sock'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m  \u001b[0;31m# AppEngine might not have  `.sock`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 839\u001b[0;31m             \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    840\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    841\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_verified\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/urllib3/connection.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    299\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    300\u001b[0m         \u001b[0;31m# Add certificate verification\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 301\u001b[0;31m         \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_new_conn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    302\u001b[0m         \u001b[0mhostname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhost\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    303\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/urllib3/connection.py\u001b[0m in \u001b[0;36m_new_conn\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    157\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    158\u001b[0m             conn = connection.create_connection(\n\u001b[0;32m--> 159\u001b[0;31m                 (self._dns_host, self.port), self.timeout, **extra_kw)\n\u001b[0m\u001b[1;32m    160\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    161\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mSocketTimeout\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/urllib3/util/connection.py\u001b[0m in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address, socket_options)\u001b[0m\n\u001b[1;32m     68\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0msource_address\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     69\u001b[0m                 \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource_address\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m             \u001b[0msock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msa\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0msock\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# 运行函数，获取结果\n",
    "crawl_dxy_data()\n",
    "crawl_statistics_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 验证结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "# 读取数据文件\n",
    "datafile = 'statistics_data.json'\n",
    "with open(datafile, 'r', encoding='UTF-8') as file:\n",
    "    json_dict = json.loads(file.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 查看广东最新5天数据\n",
    "for val in json_dict['广东'][-5:]:\n",
    "#     print(val)\n",
    "    print(f\"\"\"\n",
    "    +++++++++++++++++++++++++++++++++++\n",
    "    日期：{val['dateId']}                                          \n",
    "    总确诊人数：{val['confirmedCount']}  治愈人数：{val['curedCount']}\n",
    "    当前确诊人数：{val['currentConfirmedCount']}  当前疑似人数：{val['suspectedCount']}\n",
    "    +++++++++++++++++++++++++++++++++++\n",
    "    \"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 例子2\n",
    "\n",
    "获取国外数据,输出确诊人数前10的国家"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 爬取数据\n",
    "\n",
    "response = requests.get('https://ncov.dxy.cn/ncovh5/view/pneumonia') #request.get()用于请求目标网站\n",
    "print(response.status_code)                                          # 打印状态码\n",
    "\n",
    "try:\n",
    "    url_text = response.content.decode()                             #更推荐使用response.content.deocde()的方式获取响应的html页面\n",
    "    #print(url_text)\n",
    "    url_content = re.search(r'window.getListByCountryTypeService2true = (.*?)}]}catch',  \n",
    "                            url_text, re.S)                         \n",
    "\n",
    "    texts = url_content.group()                                     \n",
    "    content = texts.replace('window.getListByCountryTypeService2true = ', '').replace('}catch', '') \n",
    "    json_data = json.loads(content)                                        \n",
    "except:\n",
    "    print('<Response [%s]>' % response.status_code)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 输出结果\n",
    "top10_confirmedCount = [0]*10\n",
    "for item in json_data:\n",
    "    try:\n",
    "        if item['confirmedCountRank'] < 11:\n",
    "            top10_confirmedCount[item['confirmedCountRank']-1] = item\n",
    "            #print(item['confirmedCountRank'], item['provinceName'], item['currentConfirmedCount'], item['confirmedCount'])\n",
    "    except Exception as e:\n",
    "        pass\n",
    "\n",
    "for item in top10_confirmedCount:\n",
    "    print(item['confirmedCountRank'], item['provinceName'], \"当前感染人数\", item['currentConfirmedCount'], \"总感染人数\", item['confirmedCount'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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